• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.668-669
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• 2008

In this paper, we introduce various coarse-grained elastic network modeling (ENM) techniques as a novel computational method for simulating atomic scale dynamics in macromolecules including DNA, RNA, protein, and polymer. In ENM, a system is modeled as a spring network among representative atoms in which each linear elastic spring is well designed to replace both bonded and nonbonded interactions among atoms in the sense of quantum mechanics. Based on this simplified system, a harmonic Hookean potential is defined and used for not only calculating intrinsic vibration modes of a given system, but also predicting its anharmonic conformational change, both of which are strongly related with its functional features. Various nano and bio applications of ENM such as fracture mechanics of nanocomposite and protein dynamics show that ENM is one of promising tools for simulating atomic scale dynamics in a more effective and efficient way comparing to the traditional molecular dynamics simulation.

• 대한화학회지
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• 제58권6호
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• pp.543-552
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• 2014

A quantitative structure activity relationship (QSAR) study is performed for modeling and prediction of oral bioavailabilities of 216 diverse set of drugs. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM) and random forest (RF) techniques. Comparison between statistical parameters of these models indicates the suitability of SVM over other models. The root mean square errors of SVM model were 5.933 and 4.934 for training and test sets, respectively. Robustness and reliability of the developed SVM model was evaluated by performing of leave many out cross validation test, which produces the statistic of $Q^2_{SVM}=0.603$ and SPRESS = 7.902. Moreover, the chemical applicability domains of model were determined via leverage approach. The results of this study revealed the applicability of QSAR approach by using SVM in prediction of oral bioavailability of drugs.

• 한국분말재료학회지
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• 제22권4호
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• pp.247-253
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• 2015

The sintering mechanisms of nanoscale copper powders have been investigated. A molecular dynamics (MD) simulation with the embedded-atom method (EAM) was employed for these simulations. The dimensional changes for initial-stage sintering such as characteristic lengths, neck growth, and neck angle were calculated to understand the densification behavior of copper nano-powders. Factors affecting sintering such as the temperature, powder size, and crystalline misalignment between adjacent powders have also been studied. These results could provide information of setting the processing cycles and material designs applicable to nano-powders. In addition, it is expected that MD simulation will be a foundation for the multi-scale modeling in sintering process.

• Nuclear Engineering and Technology
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• 제36권3호
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• pp.229-236
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• 2004

Radiation hardening is a multiscale phenomenon involving various processes over a wide range of time and length. We present a multiscale model for estimating the amount of radiation hardening in pressure vessel steel in the environment of a light water reactor. The model comprises two main parts: molecular dynamics (MD) simulation and a point defect cluster (PDC) model. The MD simulation was used to investigate the primary damage caused by displacement cascades. The PDC model mathematically formulates interactions between point defects and their clusters, which explains the evolution of microstructures. We then used a dislocation barrier model to calculate the hardening due to the PDCs. The key input for this multiscale model is a neutron spectrum at the inner surface of reactor pressure vessel steel of the Younggwang Nuclear Power Plant No.5. A combined calculation from the MD simulation and the PDC model provides a convenient tool for estimating the amount of radiation hardening.

• 한국수산과학회지
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• 제44권2호
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• pp.167-172
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• 2011

A three-dimensional ecological model (EMT-3D) was applied to Tokyo Bay to simulate 4,4'-bis (2-sulfostyryl)biphenyl (DSBP). The simulated results were in good agreement with the observed values, with a correlation coefficient of R=0.8431 and a coefficient of determination of $R^2$=0.7108. The sensitivity analysis indicated that the photolysis rate is the most important factor. Therefore, the parameters must be considered carefully in modeling. The mass balance results showed that the standing stock of DSBP in water and in particulate organic carbon was 621.2 and 19.5 kg, respectively, and the effluent flux to the open sea was 2.63 and 0.055 kg/day, respectively.

• 한국환경과학회지
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• 제11권7호
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• pp.737-742
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• 2002

Sorption and desorption is an important phenomenon to determine the fate of halogenated aliphatic hydrocarbons in the aqueous phase. This study was conducted to develope a predictive equation capable of estimating the sorption and desorption potentials of halogenated aliphatic hydrocarbons onto the sludge from activated process, sediment, and clay. It has shown that the sorption and desorption parameters can be accurately estimated using Quantitative Structural Activity Relationship(QSAR) models based on molecular connectivity indexes of test compounds. The QSAR model could be applied to predict the sorption and desorption capacity of the other halogenated aliphatic hydrocarbons. The QSAR modeling would provide a useful tool to predict the sorption and desorption capacity without time-consuming experiments.

• 한국전기화학회:학술대회논문집
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• 한국전기화학회 2004년도 수소연료전지공동심포지움 2004논문집
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• pp.287-292
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• 2004

In order to understand the relationship between molecular structure of Metal-Organic Framework(MOF) and capacity of hydrogen absorption, quantum mechanical calculations and grand canonical Monte Carlo simulations have been carried out on a series of MOF-5 having various organic linkers. The calculation results about specific surface area and electron density for various frameworks indicated that the capacity of the hydrogen storage is largely dependent on effective surface area rather than the free volume. Based on the iso-electrostatic potential surface from density functional calculation and the amount of adsorbed hydrogens from grand canonical Monte Carlo calculation, it was also found that the electron localization ground organic linker plays an important role in hydrogen capacity of MOFs.

• Genomics & Informatics
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• 제19권2호
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• pp.18.1-18.8
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• 2021

G protein–coupled receptors (GPCRs), including olfactory receptors, account for the largest group of genes in the human genome and occupy a very important position in signaling systems. Although olfactory receptors, which belong to the broader category of GPCRs, play an important role in monitoring the organism's surroundings, their actual three-dimensional structure has not yet been determined. Therefore, the specific details of the molecular interactions between the receptor and the ligand remain unclear. In this report, the interactions between human olfactory receptor 1A1 and its odorant molecules were simulated using computational methods, and we explored how the chemically simple odorant molecules activate the olfactory receptor.

• Genomics & Informatics
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• 제19권1호
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• pp.9.1-9.5
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• 2021

Mammalian olfactory receptors are a family of G protein-coupled receptors (GPCRs) that occupy a large part of the genome. In human genes, olfactory receptors account for more than 40% of all GPCRs. Several types of GPCR structures have been identified, but there is no single olfactory receptor whose structure has been determined experimentally to date. The aim of this study was to model the interactions between an olfactory receptor and its ligands at the molecular level to provide hints on the binding modes between the OR2W1 olfactory receptor and its agonists and inverse agonists. The results demonstrated the modes of ligand binding in a three-dimensional model of OR2W1 and showed a statistically significant difference in binding affinity to the olfactory receptor between agonists and inverse agonists.

• Journal of Genetic Medicine
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• 제9권2호
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• pp.67-72
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• 2012

The generation of induced pluripotent stem cells (iPSCs) derived from patients' somatic cells provides a new paradigm for studying human genetic diseases. Human iPSCs which have similar properties of human embryonic stem cells (hESCs) provide a powerful platform to recapitulate the disease-specific cell types by using various differentiation techniques. This promising technology has being realized the possibility to explore pathophysiology of many human genetic diseases at the molecular and cellular levels. Furthermore, disease-specific human iPSCs can also be used for patient-based drug screening and new drug discovery at the stage of the pre-clinical test in vitro. In this review, we summarized the concept and history of cellular reprogramming or iPSC generation and highlight recent progresses for disease modeling using patient-specific iPSCs.